Sensitivity - Local index to control chaoticity or gradient globally.

Here, we introduce a fully local index named "sensitivity" for each neuron to control chaoticity or gradient globally in a neural network (NN). We also propose a learning method to adjust it named "sensitivity adjustment learning (SAL)". The index is the gradient magnitude of its output with respect to its inputs.

Adaptive balancing of exploration and exploitation around the edge of chaos in internal-chaos-based learning.

This paper addresses learning with exploration driven by chaotic internal dynamics of a neural network. Hoerzer et al. showed that a chaotic reservoir network (RN) can learn with exploration driven by external random noise and a sequential reward.